


default search action
3. AES International Conference Semantic Audio 2017: Erlangen, Germany
- Christian Dittmar, Jakob Abeßer, Meinard Müller:
AES International Conference Semantic Audio 2017, Erlangen, Germany, June 22-24, 2017. Audio Engineering Society 2017, ISBN 978-1-942220-15-2
Papers
- Diego Di Carlo, Ken Déguernel, Antoine Liutkus:
Gaussian Framework for Interference Reduction in Live Recordings. - Delia Fano Yela, Sebastian Ewert, Derry Fitzgerald, Mark B. Sandler:
On the Importance of Temporal Context in Proximity Kernels: A Vocal Separation Case Study. - Athanasios Lykartsis, Stefan Weinzierl, Volker Dellwo:
Speaker Identification for Swiss German with Spectral and Rhythm Features. - Andy Pearce, Tim Brookes, Russell Mason:
Timbral Attributes for Sound Effect Library Searching. - Patricio López-Serrano, Christian Dittmar, Meinard Müller:
Mid-Level Audio Features Based on Cascaded Harmonic-Residual-Percussive Separation. - Rachel M. Bittner, Justin Salamon, Juan J. Bosch, Juan Pablo Bello
:
Pitch Contours as a Mid-Level Representation for Music Informatics. - Rodrigo Schramm, Emmanouil Benetos:
Automatic Transcription of a Cappella recordings from Multiple Singers. - Amruta Vidwans, Siddharth Gururani, Chih-Wei Wu, Vinod Subramanian, Rupak Swaminathan, Alexander Lerch:
Objective Descriptors for the Assessment of Student Music Performances. - Dasaem Jeong, Juhan Nam:
Note Intensity Estimation of Piano Recordings by Score-Informed NMF. - Emmanouil Benetos:
Polyphonic Note and Instrument Tracking Using Linear Dynamical Systems. - Rainer Kelz, Gerhard Widmer:
An Experimental Analysis of the Entanglement Problem in Neural-Network-based Music Transcription Systems. - Jakob Abeßer, Stefan Balke, Klaus Frieler, Martin Pfleiderer, Meinard Müller:
Deep Learning for Jazz Walking Bass Transcription. - Alice Cohen-Hadria, Geoffroy Peeters:
Music Structure Boundaries Estimation Using Multiple Self-Similarity Matrices as Input Depth of Convolutional Neural Networks. - Gerhard Hagerer, Vedhas Pandit, Florian Eyben, Björn W. Schuller:
Enhancing LSTM RNN-Based Speech Overlap Detection by Artificially Mixed Data. - Gökhan Sevkin, Alexandra Craciun, Tom Bäckström:
An Unsupervised Hybrid Approach for Online Detection of Sound Scene Changes in Broadcast Content. - Adán L. Benito, Joshua D. Reiss:
Intelligent Multitrack Reverberation Based on Hinge-Loss Markov Random Fields. - Zdenek Prusa:
The Phase Retrieval Toolbox. - Joren Six, Marc Leman:
A Framework to Provide Fine-Grained Time-Dependent Context for Active Listening Experiences. - Jong Wook Kim, Spencer Russell, Juan Pablo Bello
:
Fast Music and Audio Processing Using the Julia Language. - Nicholas Jillings, Ryan Stables:
Investigating Music Production Using a Semantically Powered Digital Audio Workstation in the Browser. - Florian Scholz, Igor Vatolkin, Günter Rudolph:
Singing Voice Detection across Different Music Genres. - Frank Zalkow, Christof Weiß, Thomas Prätzlich, Vlora Arifi-Müller, Meinard Müller:
A Multi-Version Approach for Transferring Measure Annotations between Music Recordings. - Kumar Ashis Pati, Alexander Lerch:
A Dataset and Method for Guitar Solo Detection in Rock Music. - Jose J. Valero-Mas, Emmanouil Benetos, José Manuel Iñesta Quereda:
Assessing the Relevance of Onset Information for Note Tracking in Piano Music Transcription. - Ángel Faraldo, Sergi Jordà, Perfecto Herrera:
A Multi-Profile Method for Key Estimation in EDM. - Filip Korzeniowski, Gerhard Widmer:
On the Futility of Learning Complex Frame-Level Language Models for Chord Recognition. - Meinard Müller, Sebastian Rosenzweig, Jonathan Driedger, Frank Scherbaum:
Interactive Fundamental Frequency Estimation with Applications to Ethnomusicological Research.

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.